Breast cancer, the most commonly diagnosed cancer in American women, is a heritable disease with nearly one hundred known genetic risk factors. Using next generation sequencing, we explored the contribution of genetics at 12 GWAS-identified loci to breast cancer susceptibility in a multi-ethnic breast cancer case-control study. Methods: The study population consists of 4,611 breast cancer cases and controls (2,316 cases and 2,295 controls) from four mutually exclusive ethnicities: African, Latina, Japanese, or European American.We conducted rare variant association testing between sequenced genotypes and simulated phenotypes to compare the performance of several approaches for assessing rare variant associations across multiple ethnicities and the statistical performance of different ethnic sampling fractions, including single-ethnicity studies and studies that sample up to four ethnicities. Findings from simulation of causal rare variant penetrance models were then applied to a non-synonymous protein-coding rare variant association study of breast cancer. Next, we applied variance partitioning methods to determine what proportion of breast cancer heritability is explained by rare and common, coding and non-coding, and the complete set of sequenced genetic variants. Results: Variance component-based tests were better powered in several scenarios. Multi-ethnic studies were well powered, with inclusion of African Americans providing the largest gains in statistical power. Rare variation in several genes was nominally associated (alpha=0.05) with breast cancer risk. Common variants explained a significant amount of breast cancer heritability (5%; SE=2%). Total breast cancer heritability from all sequenced SNVs from all 12 loci was approximately 11% (S.E.=4%), a substantial portion of breast cancer heritability which ranges from 27% to 32% in European familial studies. Conclusion: Our findings suggest that association studies between rare variants and complex disease should consider including subjects from multiple ethnicities, with preference given to genetically diverse groups. We demonstrate practices with the potential to uncover and localize gene-based associations using gene-based rare variant association testing at 12 GWAS-identified breast cancer susceptibility loci. We also present strong evidence that just this subset of previously-identified loci explains a substantial portion of heritability which suggests that all GWAS-identified loci may explain more breast cancer heritability than the 17% previously reported.